Hermes Agent is an open-source autonomous AI agent framework developed by Nous Research, released in February 2026 under the MIT license. It is not a simple chatbot or an IDE-bound code completion tool — it is a persistent, self-hosted AI agent that runs on your own server 24/7 and gets smarter the more you use it.
Within just two months of its launch, Hermes Agent surpassed 60,000 stars on GitHub, making it the fastest-growing open-source project in the AI Agent space in 2026.
Official tagline:
The agent that grows with you.
All data — memories, skills, conversation history — is stored in a local SQLite database on your own machine. Nothing passes through third-party cloud services. You retain complete ownership and control over your data.
Unlike most AI assistants that "forget everything" after each session, Hermes Agent features cross-session persistent memory powered by FTS5 full-text search. It remembers your project preferences from last week and can recall task details from three months ago.
Hermes Agent includes a built-in closed-loop learning system. After completing complex tasks (typically involving 5+ tool calls), it automatically distills successful workflows into reusable "Skills." The next time it encounters a similar task, efficiency multiplies.
This is the single most differentiating capability of Hermes Agent — and the reason it's called a "self-evolving" agent.
How it works:
Observe → Execute → Reflect → Crystallize → Reuse
↑ │
└────────── Automatically invoked next ─────┘
After completing a complex task, the agent enters an automatic reflection phase: it reviews the execution process, identifies reusable patterns, and stores them as persistent skills. This is not simple template reuse — the agent dynamically adjusts variables within skills based on new context parameters.
| Layer | Type | Purpose | Lifespan |
|---|---|---|---|
| Layer 1 | Working Memory | Current session context | Single session |
| Layer 2 | Episodic Memory | Cross-session facts and preferences | Permanent |
| Layer 3 | Procedural Memory | Auto-created reusable skills | Permanent + iterative |
All memory entries undergo security scanning before storage, detecting potential prompt injection attacks and data exfiltration patterns.
The skill system uses a three-level progressive loading strategy to optimize token usage:
The skill system is compatible with the agentskills.io open standard. The community has already published hundreds of ready-to-use skill packs covering DevOps, development, content creation, data analysis, and more.
Hermes Agent supports 14+ messaging platforms with a single deployment:
| Category | Platforms |
|---|---|
| International | Telegram, Discord, Slack, WhatsApp, Signal |
| Enterprise (China) | Feishu (Lark), WeCom, DingTalk |
| Other | Matrix, Mattermost, QQ Bot, iMessage, Home Assistant, Email, SMS |
| Web | Built-in Web UI, Open WebUI |
Most importantly, conversations are continuous across platforms. A task started on Telegram can be seamlessly continued on Feishu — powered by the unified memory system.
| Environment | Characteristics | Best For |
|---|---|---|
| Local Terminal | Direct host execution | Personal dev, quick tests |
| Docker Container | Isolated, high security | Production recommended |
| E2B Cloud Sandbox | Remote isolation | Untrusted code execution |
| SSH Remote | Operate remote servers | DevOps scenarios |
Complemented by a five-level permission control model, ranging from "read-only" to "fully autonomous."
Supports 200+ models with no vendor lock-in:
You can assign different models to different task types — use Claude for complex reasoning and DeepSeek for daily conversations — achieving the optimal balance between cost and quality.
| Use Case | Examples | Recommended Deployment |
|---|---|---|
| Personal Dev Assistant | Code review, project management, bug triage | Local / Cloud |
| Content Creation Engine | Article drafting, SEO optimization, social media scheduling | Cloud |
| Enterprise Office Bot | Feishu/WeCom Q&A, daily reports, meeting summaries | Cloud (24/7) |
| Data Analyst | Scheduled data collection, report generation, anomaly alerts | Cloud |
| DevOps On-Call | Server monitoring, log analysis, auto-remediation | Cloud (24/7) |
| Learning Coach | Personalized study plans, scheduled practice prompts | Local / Cloud |
| Financial Monitor | Stock tracking, portfolio analysis, news aggregation | Cloud |
| E-Commerce Operations | Competitor monitoring, automated customer service, review analysis | Cloud |
| Dimension | Hermes Agent | OpenClaw |
|---|---|---|
| Core Positioning | Self-evolving personal agent | AI coding assistant |
| Learning System | ✅ Built-in closed-loop learning | ❌ None |
| Memory System | ✅ Three-layer persistent + FTS5 | ⚠️ Basic context |
| Auto Skill Creation | ✅ Auto-create + iterate | ❌ Manual config |
| Runtime Mode | Background daemon (24/7) | On-demand |
| Messaging Platforms | 14+ IM platforms | IDE-centric |
| IDE Integration | ⚠️ Basic | ✅ Deep VS Code integration |
| Model Support | 200+ (including Chinese models) | Mainstream commercial only |
| Data Storage | Fully local SQLite | Cloud + local hybrid |
The fundamental difference: Hermes Agent is built for long-term collaboration — it gets smarter over time and meets you wherever you are. OpenClaw excels at in-IDE programming assistance. They can coexist: use OpenClaw when coding in your IDE, and Hermes Agent for everything else.
┌──────────────────────────────────────────────────┐
│ Messaging Gateway Layer │
│ Telegram | Feishu | WeCom | Discord | Slack... │
└──────────────────┬───────────────────────────────┘
│
┌──────────────────▼───────────────────────────────┐
│ Core Engine Layer │
│ Memory System | Skills Engine | Learning Loop │
│ Cron Scheduler | Security Controls | MCP │
│ Model Router │
└──────────────────┬───────────────────────────────┘
│
┌──────────────────▼───────────────────────────────┐
│ Execution Layer │
│ Local Terminal | Docker | E2B | SSH │
└──────────────────────────────────────────────────┘
| Parameter | Value |
|---|---|
| GitHub Stars | 60,000+ (as of April 2026) |
| Supported Models | 200+ |
| Messaging Platforms | 14+ |
| Built-in Tools | 40+ |
| License | MIT (commercial use allowed) |
| Runtime | macOS / Linux / WSL2 / Termux |
| Data Storage | Local SQLite |
| Contributors | 207+ |
| Release Cadence | ~Every 2 weeks |
curl -fsSL https://hermes-agent.org/install.sh | bash
hermes init
hermes start
Supports macOS 12+, Ubuntu 20.04+, and Windows WSL2. Requires Python 3.11+ and Node.js 18+.
For always-on scenarios (enterprise bots, DevOps monitoring, financial alerts), deploy Hermes Agent on a cloud server. A minimal 2-core, 2 GB configuration is sufficient.
Quick start — just three steps:
Step 1: Purchase a cloud server → Step 2: One-click install Hermes Agent → Step 3: Connect messaging platforms and start using
docker run -d --name hermes-agent \
--restart unless-stopped \
-v ~/.hermes:/root/.hermes \
-p 3000:3000 \
nousresearch/hermes-agent:latest
ollama pull qwen2.5:7b
hermes config set model.provider ollama
hermes config set model.model qwen2.5:7b
Configure all platforms at once with the interactive setup wizard:
hermes gateway setup
| Platform | Difficulty | Setup Time |
|---|---|---|
| Telegram | ⭐ Easiest | 5 minutes |
| Feishu (Lark) | ⭐⭐ Medium | 15 minutes |
| WeCom | ⭐⭐ Medium | 15 minutes |
| DingTalk | ⭐⭐ Medium | 15 minutes |
| Discord | ⭐ Easy | 5 minutes |
Extend Hermes Agent's capabilities infinitely through the Model Context Protocol (MCP):
Ready to experience Hermes Agent? Deploy it on a cloud server for the best 24/7 experience:
👉 Tencent Cloud — Hermes Agent Server: https://www.tencentcloud.com/act/pro/lighthouse
👉 Step-by-Step Deployment Tutorial: https://www.tencentcloud.com/techpedia/143916